title: Dosimetric comparison of helical tomotherapy treatment plans for total marrow irradiation created using GPU and CPU dose calculation engines.
abstract: OBJECTIVE
  To compare optimization characteristics, plan quality, and treatment delivery efficiency between total marrow irradiation (TMI) plans using the new TomoTherapy graphic processing unit (GPU) based dose engine and CPU/cluster based dose engine.
  
  
  METHODS
  Five TMI plans created on an anthropomorphic phantom were optimized and calculated with both dose engines. The planning treatment volume (PTV) included all the bones from head to mid femur except for upper extremities. Evaluated organs at risk (OAR) consisted of lung, liver, heart, kidneys, and brain. The following treatment parameters were used to generate the TMI plans: field widths of 2.5 and 5 cm, modulation factors of 2 and 2.5, and pitch of either 0.287 or 0.43. The optimization parameters were chosen based on the PTV and OAR priorities and the plans were optimized with a fixed number of iterations. The PTV constraint was selected to ensure that at least 95% of the PTV received the prescription dose. The plans were evaluated based on D80 and D50 (dose to 80% and 50% of the OAR volume, respectively) and hotspot volumes within the PTVs. Gamma indices (Γ) were also used to compare planar dose distributions between the two modalities. The optimization and dose calculation times were compared between the two systems. The treatment delivery times were also evaluated.
  
  
  RESULTS
  The results showed very good dosimetric agreement between the GPU and CPU calculated plans for any of the evaluated planning parameters indicating that both systems converge on nearly identical plans. All D80 and D50 parameters varied by less than 3% of the prescription dose with an average difference of 0.8%. A gamma analysis Γ(3%, 3 mm) < 1 of the GPU plan resulted in over 90% of calculated voxels satisfying Γ < 1 criterion as compared to baseline CPU plan. The average number of voxels meeting the Γ < 1 criterion for all the plans was 97%. In terms of dose optimization/calculation efficiency, there was a 20-fold reduction in planning time with the new GPU system. The average optimization/dose calculation time utilizing the traditional CPU/cluster based system was 579 vs 26.8 min for the GPU based system. There was no difference in the calculated treatment delivery time per fraction. Beam-on time varied based on field width and pitch and ranged between 15 and 28 min.
  
  
  CONCLUSIONS
  The TomoTherapy GPU based dose engine is capable of calculating TMI treatment plans with plan quality nearly identical to plans calculated using the traditional CPU/cluster based system, while significantly reducing the time required for optimization and dose calculation.
authors.affiliation: Karmanos Cancer Center, Detroit, Michigan 48201, USA. nalichoa@karmanos.org
authors.forename: Adrian
authors.initials: A
authors.lastname: Nalichowski
authors.forename: Jay
authors.initials: J
authors.lastname: Burmeister
mesh_terms: D001853:Bone Marrow / Q000528:radiation effects*; D003196:Computer Graphics; D003201:Computers; D058958:Organs at Risk / Q000528:radiation effects; D011829:Radiation Dosage; D011874:Radiometry; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*